DocumentCode :
2774665
Title :
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Author :
Jun, Goo ; Vatsavai, Ranga Raju ; Ghosh, Joydeep
Author_Institution :
Dept. of ECE, Univ. of Texas at Austin, Austin, TX, USA
fYear :
2009
fDate :
6-6 Dec. 2009
Firstpage :
597
Lastpage :
603
Abstract :
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and spectral characteristics of each class often varies over time and space. We apply a spatially adaptive classification scheme that models spatial variation with Gaussian processes, and apply uncertainty sampling based active learning algorithm to achieve better classification accuracies with a fewer number of samples. The spatially adaptive classifier shows better performances than the conventional maximum likelihood classifier in both passive and active learning settings, and the active learners achieves better classification accuracies than passive learners with fewer number of samples for both classification algorithms.
Keywords :
Gaussian processes; geophysical image processing; land use planning; learning (artificial intelligence); maximum likelihood estimation; pattern classification; remote sensing; Gaussian processes; active learning; automated land cover classification tasks; automated land use classification tasks; maximum likelihood classifier; multispectral data; multispectral remote sensing images; spatially adaptive classification; uncertainty sampling; Computer science; Conferences; Data mining; Detection algorithms; Distributed algorithms; Gaussian processes; Monitoring; NASA; Space technology; Statistical distributions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops, 2009. ICDMW '09. IEEE International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-5384-9
Electronic_ISBN :
978-0-7695-3902-7
Type :
conf
DOI :
10.1109/ICDMW.2009.107
Filename :
5360481
Link To Document :
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